An Empirical Model for Forecasting Maximum Daily Ozone Levels in the Northeastern U.S.

Ozone Air Quality over North America: Part I—A Review of Reported Trends

“…The third problem hampering O 3 trend analyses is the strong influence meteorology has on O 3 concentrations. The effect has been well documented (see, e.g., Wolff et al, 6 Wolff and Lioy, 7 and Chock et al 8 ). The variability in O 3 induced by the variability in meteorological conditions is much larger than that due to changes in emissions in the last two decades.…”

Using National Air Quality Forecast Guidance to Develop Local Air Quality Index Forecasts

“…During this and the following decade, numerous state and municipal air quality agencies developed basic forecasting approaches in an attempt to reduce exposure, thereby reducing the impact of poor air quality on human health. These forecasts, which generally focused on urban scales, were often based on statistical models that forecast pollutant concentrations based on equations that had been trained or fitted to historical air quality [most often ozone (O 3 )] and meteorological data (McCollister and Wilson 1975;Aron and Aron 1978;Wolff and Lioy 1978;Lin 1982;Robeson and Steyn 1990). These approaches worked best under persistent meteorological conditions, but generally performed poorly in forecasting the onset and/or termination of a pollution episode.…”

Interpolation of temperature and non-urban ozone exposure at high spatial resolution over the western United States

“…The NCDC meteorological stations have good spatial coverage at lower elevations Because O 3 formation and transport are dependent upon radiant energy and atmospheric conditions, O 3 concentrations correlate well with atmospheric variables. Many studies of O 3 concentrations and meteorology in rural and urban areas in the United States have found that ambient air temperature was the most important variable for modeling trends in O 3 concentrations or identifying high ozone days (Wolff & Lioy 1978, Chock et al 1982, Kuntasal & Chang 1987, National Research Council 1992, Eder et al 1994, Van Ooy & Carroll 1995, Bloomfield et al 1996. The monthly mean daily maximum temperature met our objective of using a highly correlated auxiliary variable for the interpolation of the monthly SUM06 exposure index in non-urban areas in the western United States.…”